Use of aggregated relational data in agent-based modeling

Aggregated relational data (ARD) provides valuable information for inferring structural features of personal social networks at scale. Following recent ARD studies, we suggest a formal parameter for agent-based modeling (ABM) that helps reflect multiple structural features of extended social networks (e.g., size; variation; distribution) and apply it to a widely known classic ABM—Axelrod’s cultural dynamic model. Results show that when incorporating realistic network features estimated from ARD, the model generates outcomes substantially different from its original results. Our study highlights ARD's potential to enrich ABM in reflecting more realistic networks that better connect micro-processes with macro-phenomena. • We suggest an ARD-informed parameter for network modeling in ABMs. • It structures long-range ties in small-world networks using recent ARD findings. • The mean, variation, and skewness of long-range tie distribution are customizable. • A small-world network with the parameter is applied to Axelrod’s culture model. • Results differ substantially from Axelrod’s model using a classic small-world.